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Product Updates August 12, 2026

Bridging AI and Infrastructure: Introducing MCP Support in Base44

We are bringing the Model Context Protocol to Base44, enabling your AI agents to seamlessly interact with your internal data models and enterprise connectors.

Bridging AI and Infrastructure: Introducing MCP Support in Base44

The New Frontier of Agentic Workflows

For the past year at Base44, we’ve been obsessed with one goal: stripping away the friction between a founder's vision and a deployed, production-grade application. We’ve built a platform that handles the heavy lifting—managed backends, authentication, RLS, and native mobile exports—so you can focus on shipping. But today, we’re leveling up how your AI interacts with that infrastructure.

I’m excited to announce that Base44 now supports the Model Context Protocol (MCP). By standardizing how your agents connect to your database entities and external tools, we’re removing the 'connector tax' that slows down complex automation.

Why MCP Matters for Base44 Builders

Previously, integrating AI agents meant writing custom glue code for every tool or entity you wanted to manipulate. With MCP, Base44 exposes your defined entities—like your CRM rows or inventory records—as a standard interface for any MCP-compliant agent.

If you have a Product entity defined as a typed JSON schema, your agent doesn’t just 'know' about it; it has a formal, validated contract to perform base44.entities.Product.create, filter, or update operations. This isn't just about reading data; it’s about providing your agents with reliable, tool-use capabilities using the same RLS logic you already trust for your users.

A Practical Walkthrough: Automating Inventory with Superagents

Let’s say you’re building an e-commerce dashboard. You have an entity InventoryItem and you want an AI Superagent to manage stock alerts across Slack and Email.

  1. Define the Schema: You define your InventoryItem with the necessary fields in the Base44 editor.
  2. Expose via MCP: Once connected, your agent is granted managed tool permissions. It sees the base44.entities.InventoryItem schema as a native tool.
  3. Deploy Workflow: You set up a triggered workflow using the entity events hook. When stock drops below a threshold, the workflow triggers your Superagent.
  4. Execute: The agent, utilizing InvokeLLM (configured with claude_sonnet_4_6), checks the current InventoryItem records via MCP, generates a report, and uses the Slack connector to notify your ops team.

Because we built this on our core platform, your agent retains memory and context, allowing it to act proactively rather than just responding to prompts.

Beyond the Text Box

Integrating MCP into the Base44 ecosystem means your AI agents are no longer just chatbots; they are authenticated, authorized operators of your business logic. Whether you are building internal tools with React and shadcn/ui or complex automated CRMs, your agents now speak the same language as your database.

This is how we move toward a world where 'software development' is simply describing a process to a system that understands the underlying data structures. We aren't just generating code anymore; we are orchestrating business operations at scale.

What’s Next?

We’ve already pushed these updates to your Base44 dashboard. Go ahead and map your existing entities to the new MCP interface. If you run into bottlenecks or have ideas on how we can tighten the feedback loop between agents and connectors, ping me on the community channels.

We’re building this for the founders who move fast. Let’s see what you automate this week.